ABSTRACT

Context Adiponectin, a recently discovered adipocyte-derived peptide, is involved
in the regulation of insulin sensitivity and lipid oxidation and, purportedly,
in the development of atherosclerosis and coronary heart disease in humans.

Design, Setting, and Participants Nested case-control study among 18 225 male participants of the
Health Professionals Follow-up Study aged 40 to 75 years who were free of
diagnosed cardiovascular disease at the time of blood draw (1993-1995). During
6 years of follow-up through January 31, 2000, 266 men subsequently developed
nonfatal MI or fatal coronary heart disease. Using risk set sampling, controls
were selected in a 2:1 ratio matched for age, date of blood draw, and smoking
status (n = 532).

Results After adjustment for matched variables, participants in the highest
compared with the lowest quintile of adiponectin levels had a significantly
decreased risk of MI (relative risk [RR], 0.39; 95% confidence interval [CI],
0.23-0.64; P for trend <.001). Additional adjustment
for family history of MI, body mass index, alcohol consumption, physical activity,
and history of diabetes and hypertension did not substantively affect this
relationship (RR, 0.41; 95% CI, 0.24-0.70; P for
trend <.001). Further adjustment for hemoglobin A1c or C-reactive
protein levels also had little impact, but additional adjustment for low-
and high-density lipoprotein cholesterol levels modestly attenuated this association
(RR, 0.56; 95% CI, 0.32-0.99; P for trend = .02).

Conclusions High plasma adiponectin concentrations are associated with lower risk
of MI in men. This relationship can be only partly explained by differences
in blood lipids and is independent of inflammation and glycemic status.

Figures in this Article

Adiponectin (Arcp30, AdipoQ, apM1, or GBP2 8) is a recently discovered
247 amino acid peptide, predominantly secreted by adipocytes, that accounts
for about 0.05% of total serum proteins.1- 4 It
is induced early in adipocyte differentiation,1 consists
of an N-terminal collagenous and a C-terminal globular domain, and shares
homology with subunits of complement factor C1q.1,3 Adiponectin
expression is reduced in obesity, insulin resistance, and type 2 diabetes,
and plasma concentrations are inversely related to body weight and insulin
levels, and reflect peroxisome proliferator–activated receptor γ
(PPAR-γ) activation.5- 9 Treatment
with adiponectin improves insulin sensitivity in animal models of insulin
resistance10,11 and reverses diet-induced
insulin resistance in adiponectin knockout mice.12 Low
plasma adiponectin levels have recently been shown to predict risk of developing
type 2 diabetes in humans.8,13 Adiponectin
is also inversely associated with other traditional cardiovascular risk factors,
such as blood pressure, heart rate, and total and low-density lipoprotein
(LDL) cholesterol and triglyceride levels,14,15 and
is positively related to high-density lipoprotein (HDL) cholesterol levels.14,16 Furthermore, recent studies suggest
that it may have antiatherogenic and anti-inflammatory properties.17- 22 These
data suggest that high plasma adiponectin levels may be related to a lower
risk of coronary heart disease (CHD), but data in humans are lacking. Therefore,
we conducted a case-control study nested within the Health Professionals Follow-up
Study (HPFS) to assess the association between baseline plasma adiponectin
levels and risk of myocardial infarction (MI) over a follow-up period of 6
years.

METHODS

Study Population

The HPFS is a prospective cohort investigation among 51 529 US
male health care professionals aged 40 to 75 years at baseline in 1986, designed
primarily to evaluate associations between diet and chronic disease incidence.23 Information about health and disease is assessed
biennially by a self-administered questionnaire and diet every 4 years by
a self-administered food frequency questionnaire.24 Between
1993 and 1995, a blood sample was requested from all participants and returned
by 18 225 participants. Men who provided samples were somewhat younger
but were otherwise similar to those who did not provide samples. Based on
this sample and after exclusion of participants with a history of cardiovascular
disease prior to 1994, we identified 266 participants with incident nonfatal
MI or fatal CHD between date of blood draw and return of the 2000 questionnaire
(January 2000). Controls were randomly selected from participants with a blood
sample and without history of cardiovascular disease at the time of case ascertainment
in a 2:1 ratio and matched for age, date of blood draw, and smoking status
(risk set sampling).25 Our analysis includes
1 participant who was selected as a control and subsequently had an event
during follow-up. No control was selected twice in our analysis during the
random selection process.

All participants gave written informed consent, and the Harvard School
of Public Health Human Subjects Committee Review Board approved the study
protocol.

Assessment of Nonfatal MI and Fatal CHD

Study physicians blinded to participants' exposure status reviewed the
medical records of all participants for whom nonfatal MI or fatal CHD was
ever reported. Each questionnaire that is mailed biennially to participants
of the HPFS contains a question on whether the participant has had "professionally
diagnosed . . . myocardial infarction (heart attack)" in the preceding 2 years.
Myocardial infarction was confirmed if it met the World Health Organization's
criteria (symptoms plus either diagnostic electrocardiographic changes or
elevated levels of cardiac enzymes).26 In about
70% of participants with reported MI, the diagnosis was confirmed using these
methods. Reasons for nonconfirmation were either that no further information
was available (because the participant or hospital did not consent to send
the hospital records) or that a reported case was rejected. Nonconfirmed participants
were excluded from the selection process. Deaths were identified from state
vital statistics records and the National Death Index or reported by next
of kin or the postal system. Fatal CHD was considered to have occurred if
there was fatal MI confirmed by hospital records or on autopsy or if CHD was
listed as the cause of death on the death certificate, if it was the underlying
and most plausible cause, and if evidence of previous CHD was available. In
our analysis, 196 participants had nonfatal MI and 70 had fatal CHD as the
qualifying event.

Anthropometric data, lifestyle factors, and diet were derived from the
1994 questionnaire. Body mass index was calculated as weight in kilograms
divided by the square of height in meters. Nutrient intake was computed based
on a semiquantitative food frequency questionnaire (which inquires about average
food intake during the past year) using composition values from the US Department
of Agriculture sources,27 supplemented with
other data. Physical activity was expressed as metabolic equivalent task (MET)–hours
based on self-reported types and durations of activities over the previous
year.28 One MET-hour is equivalent to energy
expenditure while sitting quietly for 1 hour. Medical history was derived
from the questionnaires between 1986 and 1994. The questionnaires and the
validity and reproducibility of the collected data and measurements have been
reported in detail elsewhere.24,29- 33

Measurement of Biochemical Variables

Blood samples were collected in three 10-mL liquid EDTA blood tubes,
placed on ice packs, stored in Styrofoam containers, and returned to our laboratory
via overnight courier, with more than 95% arriving within 24 hours. After
arrival, blood samples were centrifuged and aliquoted for storage in the vapor
phase of liquid nitrogen freezers (−130°C or colder). Fewer than
15% of the samples were slightly hemolyzed and very few were moderately hemolyzed
(<3%), lipemic (<1%), or not cooled on arrival (<0.5%).

Plasma adiponectin concentrations were measured by competitive radioimunoassay
(Linco Research Inc, St Charles, Mo) with a coefficient of variation of 3.4%
(n = 39). In a previous analysis, adiponectin levels had excellent intraclass
correlation coefficients measured in participants over a period of 1 year
and were not substantially affected by transport conditions.34

Total cholesterol was measured enzymatically35;
LDL cholesterol by a homogeneous direct method from Genzyme Corp, Cambridge,
Mass36; HDL cholesterol using a direct enzymatic
colorimetric assay37; and triglycerides enzymatically
with correction for endogenous glycerol.38 The
assays used for lipoprotein and lipid analysis are approved by the US Food
and Drug Administration for clinical use, and coefficients of variation were
less than 6%. Hemoglobin A1c (HbA1c) was measured by
turbidimetric immunoinhibition, and C-reactive protein (CRP) concentrations
were determined using an immunoturbidimetric high-sensitivity assay on a Hitachi
911 analyzer (Roche Diagnostics, Indianapolis, Ind) and reagents and calibrators
from Denka Seiken (Niigata, Japan). The laboratory used (N.R.) is certified
by the Centers for Disease Control and Prevention/National Heart, Lung, and
Blood Institute Lipid Standardization Program.

Sixty-five percent of the participants in the present analysis provided
fasting blood samples (≥8 hours since last meal; 67% among cases and 64%
among controls) (P = .36). Data on LDL cholesterol
and CRP levels were each missing in 1 participant; these values were replaced
by the median concentrations in this cohort.

Statistical Analyses

Continuous variables are presented as means and standard deviations
or medians and interquartile ranges and were compared between cases and controls
using the unpaired t test or the Wilcoxon unpaired
rank sum test. Proportions were compared using the χ2 test.
Associations between adiponectin levels and selected cardiovascular risk factors
were examined in cases and controls using an age-adjusted Spearman partial
correlation coefficient.

Adiponectin levels were categorized into quintiles based on control
participants. Unconditional logistic regression adjusted for matched variables
(age <50, 50-54, 55-59, 60-64, or ≥65 years; smoking status never, past,
or current; and month of blood draw in 5 categories) was used to investigate
the association between baseline adiponectin concentrations and incidence
of nonfatal MI or fatal CHD (events). To test for linear trend across categories,
we used log-transformed adiponectin levels. In our multivariable model, we
further adjusted for family history of MI before age 60 years (yes/no), alcohol
intake (nondrinker; 0.1-4.9, 5.0-14.9, 15.0-29.9, or ≥30.0 g/d; or missing),
body mass index (<20, 20-24, 25-29, 30-34, or ≥35), physical activity
(quintiles), and history of diabetes (yes/no) and hypertension (yes/no) at
baseline. We repeated our main analysis using conditional logistic regression
and found essentially the same results. Because of the design of our study,
the odds ratio derived from logistic regression directly estimates the incidence
rate (hazard) ratio and, therefore, the relative risk (RR).25,39

We next examined the impact of potential intermediate biomarkers by
sequentially adding LDL and HDL cholesterol and log-transformed triglyceride,
HbA1c, and CRP levels as continuous variables to our models, and
estimated the multivariable-adjusted RR associated with an increase of (continuous)
log-transformed adiponectin levels by 2 units on a log scale, which corresponds
to a doubling in adiponectin levels on the original scale.

For stratified analysis, we also calculated the multivariable-adjusted
RR associated with a doubling in adiponectin levels. We defined the metabolic
syndrome similarly as recently proposed by the National Cholesterol Education
Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High
Blood Cholesterol in Adults40 as having 3 or
more of the following 5 abnormalities: body mass index of at least 25; triglyceride
levels of at least 150 mg/dL (0.20 mmol/L); HDL cholesterol levels of less
than 40 mg/dL (1.04 mmol/L); history of hypertension; and history of diabetes,
development of diabetes during follow-up, or HbA1c levels of at
least 7% at baseline. The distribution of metabolic abnormalities in controls
in the present study was similar to that recently reported for the third National
Health and Nutrition Examination Survey (≥1 metabolic abnormalities, 77.6%
vs 71.5%; ≥2, 48.9% vs 44.9%; ≥3, 26.3% vs 24.0%; ≥4, 9.0% vs 11.1%;
and 5, 1.7% vs 2.4%).41 Results were similar
when we restricted our analysis to fasting participants only. We tested interactions
between adiponectin levels and subgroups with a cross-product term (subgroup
× log-transformed adiponectin levels) in the main effects model. Nondiscrete
variables (body mass index, LDL and HDL cholesterol, triglycerides, log CRP,
physical activity, and age) were used continuously for main effect and interaction
terms. We assessed the goodness of fit of the models using the method described
by Hosmer and Lemeshow42 and did not find any
significant lack of fit. All P values presented are
2-tailed; P<.05 was considered statistically significant.
All analyses were performed using SAS software, version 8.2 (SAS Institute
Inc, Cary, NC).

RESULTS

Characteristics and biomarker levels of cases and controls are presented
in Table 1. Cases had a nonsignificantly
higher body mass index and were more likely to have a history of hypertension
and diabetes and a family history of MI before age 60 years, although the
latter did not reach statistical significance. Cases consumed slightly less
alcohol and were less physically active than controls, although these differences
were not statistically significant. Cases had significantly lower mean adiponectin
levels than controls (15.6 [SD, 8.5] mg/L vs 17.9 [SD, 8.8] mg/L; P<.001) and, as expected, significantly higher levels of total and
LDL cholesterol, triglycerides, and HbA1c and lower HDL cholesterol
levels.

We next examined the association of adiponectin levels with selected
cardiovascular risk factors among cases and controls (Table 2). After adjustment for age, adiponectin was significantly
positively correlated with HDL cholesterol and physical activity and negatively
correlated with triglyceride, CRP, and HbA1c levels and body mass
index. Results were similar when cases and controls were combined in this
analysis.

Table 3 shows the estimated
RRs of MI during 6 years of follow-up across quintiles of adiponectin levels
at baseline. After adjustment for matched variables, participants in the highest
compared with the lowest quintile of adiponectin levels had a significantly
decreased risk of MI (RR, 0.39; 95% confidence interval [CI], 0.23-0.64; P for trend on a log scale <.001). Further adjustment
for family history of MI, body mass index, alcohol consumption, physical activity,
and history of diabetes and hypertension at baseline did not substantively
affect this relationship (RR, 0.41; 95% CI, 0.24-0.70; P for log trend <.001), whereas additional adjustment for LDL and
HDL cholesterol levels modestly attenuated the association (RR, 0.56; 95%
CI, 0.32-0.99; P for log trend = .02).

We next examined the impact of potential intermediary biomarkers on
the relation between adiponectin and risk of MI, by sequentially adding these
markers as continuous variables to our model, and calculated the multivariable-adjusted
RR associated with an increase of (continuous) log-transformed adiponectin
levels by 2 units on a log scale, which represents a doubling in adiponectin
concentrations on the original scale; however, as can be seen from Figure 1, after adjustment for LDL and HDL
cholesterol, which modestly attenuated the association, addition of triglycerides,
HbA1c, and CRP levels did not substantively affect the results.

Table 4 shows the multivariable-
and lipid-adjusted relative risk of MI associated with a doubling in adiponectin
levels in subgroups of our population. In general, the results were similar
among younger and older participants and in different strata of cardiovascular
risk factors. Because our subset included only a limited number of participants
with diabetes at baseline, we were not able to calculate effect estimates
within this subgroup; however, exclusion of these participants did not substantively
alter the results as presented in Table
4. Similarly, exclusion of participants with a parental history
of MI before age 60 years did not affect the results. Results were also similar
in different strata of alcohol consumption and physical activity and among
those taking and not taking aspirin.

Table Graphic Jump LocationTable 4. Multivariable-Adjusted Estimated
RRs of Myocardial Infarction During 6 Years of Follow-up Associated With a
Doubling in Adiponectin Level by Subgroup*

We repeated our main analysis excluding participants who developed the
qualifying event during the first 2 years of follow-up and found essentially
the same results (RR associated with a doubling in adiponectin levels, 0.77;
95% CI, 0.61-0.97; P = .02). Similarly, we found
the same results when we excluded nonfasting participants from our main analysis
(RR, 0.80; 95% CI, 0.61-1.06; P = .11) and when we
excluded current smokers (RR, 0.83; 95% CI, 0.67-1.04; P = .11). When we stratified our analysis by type of first event, we
found an inverse association between adiponectin and risk of nonfatal MI (RR,
0.73; 95% CI, 0.58-0.93; P = .009) but not risk of
fatal CHD (RR, 0.97; 95% CI, 0.67-1.41; P = .88);
however, the latter group included only 70 cases.

COMMENT

In this nested case-control study, we found high plasma adiponectin
levels associated with lower risk of MI over a follow-up period of 6 years
among men without previous cardiovascular disease. This association was independent
of traditional cardiovascular risk factors that might be associated with adiponectin
levels and, thus, are potential confounders. Of note, the relationship was
also independent of hypertension, diabetes, and HbA1c levels, factors
that were closely related to adiponectin levels in previous studies. Furthermore,
the relationship was only partly explained by differences in blood lipid levels
and was independent of CRP.

Our results are in line with previous cross-sectional studies of adiponectin
levels and coronary artery disease.5,43,44 Kumada
et al43 reported significantly lower adiponectin
levels in 225 consecutive male patients aged 40 to 69 years with coronary
artery disease compared with 225 voluntary blood donors and a 2.05-fold increased
risk of coronary artery disease (95% CI, 1.29-4.95) comparing participants
in the lowest and highest quartiles of adiponectin levels, after adjustment
for diabetes, dyslipidemia, hypertension, smoking, and body mass index. In
a study by Hotta et al,5 adiponectin levels
were lowest in participants with coronary artery disease and type 2 diabetes,
intermediate in those without diabetes, and highest in nondiabetic individuals.
These significant differences persisted after adjustment for other cardiovascular
risk factors. Kojima et al44 found significantly
lower adiponectin levels in 34 participants with acute MI compared with 35
individuals without significant coronary artery stenosis who were matched
for age, sex, and body mass index.

Among 227 hemodialysis patients, Zoccali et al45 found
in a prospective setting that after adjustment for cardiovascular risk factors,
adiponectin was inversely related to cardiovascular events (hazard ratio,
0.97; 95% CI, 0.93-0.99 for an increase in adiponectin levels of 1 mg/L) over
a mean follow-up of 2.5 years, although adiponectin levels did not predict
overall mortality. A study by Lindsay et al46 found
no significant association between plasma adiponectin levels and risk of CHD
in a nested case-control study among 372 American Indians after adjustment
for other cardiovascular risk factors (odds ratio for 1-SD change in adiponectin,
0.90; P = .34) however, in stratified analyses, they
found a significantly reduced risk among those with type 2 diabetes (comprising
about 61% of their initial data set; odds ratio, 0.40; P = .02).

As an extension to these reports, our study is among the first to suggest
that plasma adiponectin levels may predict cardiovascular events years in
advance in a population without diagnosed cardiovascular disease. In fact,
several lines of evidence suggest that adiponectin may be not only a marker
of cardiovascular risk but also a causal risk factor. First, adiponectin may
lower the risk of cardiovascular disease by improving insulin sensitivity
and blood lipid levels, as suggested by animal and human data.8,10- 13 Adiponectin
has been shown to result in activation of the adenosine monophosphate–activated
protein kinase in skeletal muscle and liver, leading to phosphorylation of
acetyl coenzyme A carboxylase, increased fatty acid oxidation and glucose
uptake, reduced fatty acid synthesis, and reduction of molecules involved
in gluconeogenesis.47 Downstream effects may
include reduced triglyceride content in liver and skeletal muscle and suppression
of hepatic glucose production.10,11,48,49 This
may also explain the finding in our study and in previous studies that adiponectin
is inversely associated with triglyceride levels and positively associated
with HDL cholesterol levels.14- 16

Third, adiponectin may modulate the vascular response to lipid and inflammatory
stimuli. Thus, adiponectin inhibits endothelial nuclear transcription factor
NF-κB signaling, which mediates the effects of TNF-α and other
cytokines.20

Furthermore, adiponectin suppresses lipid accumulation and class A scavenger
receptor expression in macrophages and, consequently, the transformation of
macrophages to foam cells, which plays an important role in the atherogenic
process.21 It was shown that adiponectin binds
to subendothelial collagens and suppresses proliferation and migration of
human aortic smooth muscle cells.22,56 In
apolipoprotein E–deficient mice, adiponectin significantly reduced the
development of atherosclerosis that usually occurs in these animals.57,58 Consistent with these animal studies,
low adiponectin levels were found in participants with coronary artery disease.5,43,45

Our study has some limitations. The inverse relationship between plasma
adiponectin levels and risk of MI was not linear but, rather, plateaued in
the middle quintiles and was most pronounced in the highest quintile; however,
we used rather conservative methods to estimate the RRs, which makes it unlikely
that our results are driven by outliers. Furthermore, this type of nonlinear
relationship is consistent with other reports on adiponectin and risk of CHD
and type 2 diabetes.13,43 A single
assessment of adiponectin may be susceptible to short-term variation, which
would bias the results toward the null. However, in a previous analysis, we
found intraindividual adiponectin levels to be reasonably stable over time,
with an intraclass correlation coefficient of 0.85 for adiponectin levels
measured within participants 1 year apart.34 It
is currently unknown whether long-term storage of blood samples affects plasma
adiponectin levels; however, if anything, this would tend to increase measurement
error and, thus, bias the results toward the null. Because the ranges of anthropometric
parameters in the present study were quite broad, the biological relationships
found should be generalizable. Future studies should address whether our findings
also apply to women and individuals with different racial/ethnic origins and
socioeconomic status and whether adiponectin levels predict cardiovascular
events beyond a follow-up period of 6 years. It is possible that the observed
association is confounded by a yet-to-be-determined factor; however, we adjusted
our analysis for established and novel cardiovascular risk factors. Furthermore,
although the results failed to reach formal statistical significance in certain
subgroups, possibly because of limited sample size, we found comparable and
robust risk reductions in various low and high cardiovascular risk groups.
While we excluded participants with diagnosed cardiovascular disease at baseline,
we cannot exclude the possibility that participants had undiagnosed atherosclerosis.
However, we found similar results when we excluded participants who developed
MI during the first 2 years of follow-up. Not all participants in our data
set provided fasting blood samples, which could affect the measurement of
triglyceride levels; however, any potential misclassification should be nondifferential.
Furthermore, results were similar when we restricted our analysis to fasting
participants. Finally, LDL cholesterol levels in our study were measured directly,36 without using the Friedewald formula, and, thus,
do not depend on fasting status. We used body mass index instead of waist-hip
ratio to assess abdominal obesity, which may lead to misclassification of
the metabolic syndrome; however, the distribution of metabolic abnormalities
was similar to that recently reported for the general population,41 and the metabolic syndrome was used for secondary
analyses only. Since plasma insulin levels were not available in our data
set, we were unable to examine the impact of this potentially intermediary
variable; however, adjustment for HbA1c as a marker of glycemic
control did not appreciably change the results. It should be noted that some
of the variables that we adjusted for may be causal mediators instead of confounders,
which would underestimate the true relationship between adiponectin levels
and risk of MI.

In conclusion, we found that high plasma adiponectin levels are associated
with a lower risk of MI over a follow-up period of 6 years among men without
previous cardiovascular disease, independent of traditional cardiovascular
disease risk factors. Particularly, this relationship can only partly be explained
by differences in blood lipids and is independent of inflammation and glycemic
status at baseline. The effect of adiponectin on risk of CHD merits further
study.

Yokota T, Oritani K, Takahashi I.
et al. Adiponectin, a new member of the family of soluble defense collagens,
negatively regulates the growth of myelomonocytic progenitors and the functions
of macrophages. Blood.2000;96:1723-1732.PubMed

Third Report of the National Cholesterol Education Program (NCEP) Expert
Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in
Adults (Adult Treatment Panel III) final report. Circulation.2002;106:3143-3421.PubMed

Yokota T, Oritani K, Takahashi I.
et al. Adiponectin, a new member of the family of soluble defense collagens,
negatively regulates the growth of myelomonocytic progenitors and the functions
of macrophages. Blood.2000;96:1723-1732.PubMed

Third Report of the National Cholesterol Education Program (NCEP) Expert
Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in
Adults (Adult Treatment Panel III) final report. Circulation.2002;106:3143-3421.PubMed

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